Bilateral Rent‐seeking and Growth of Fdi Inflow in China: Theory and Evidence

Keng, Shu; Li, Weiping; Shen, Jim Huangnan

doi:10.1111/coep.12459

Cited by 9 publications

(7 citation statements)

References 62 publications

(69 reference statements)

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“…Our theoretical findings on output dynamics along the value chains are consistent with other works in the innovation economics literature, which state that there is a positive relationship between output and firms’ expenditure on R&D (Chen & Lee, 2020; Cohen et al., 1987; Keng et al, 2020; Shefer & Frenkel, 2005). However, our model also shows that the premise of maintaining such a high level of output capacity is to ensure that firms moving towards relatively more upstream stages should not set too high a price level of intermediate goods, because this would shrink their input demand from their vertically linked downstream buyers.…”

Section: Introductionsupporting

confidence: 90%

Towards a dynamic model of the industrial upgrading with global value chains

Shen

Zhang

et al. 2020

World Economy

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This research constructs a simple dynamic model to illustrate the micro‐mechanism of industrial upgrading along the global value chains. Our model predicts that as firms move up from downstream to upstream stages, (a) there is higher profitability if and only if the following three conditions are satisfied. First, the increasing rate of sunk cost (including R&D expenditure) over sequential stages of production cannot be sufficiently large (endogenous sunk cost effect). Second, the decreasing rate of change of intermediate input demand with respect to the price set by firms at a production stage cannot be sufficiently high (intermediate input price effect). Third, the decreasing rate of change of intermediate input demand with respect to the pricing dynamics over the sequential stages of production cannot be sufficiently large (sequential pricing uncertainty effect); (b) total cost is lower if and only if the decreasing rate of change of input demand with respect to the price is sufficiently large; (c) output is higher if and only if and the decreasing rate of change of input demand with respect to the price is not sufficiently large; and (d) the price decreases. We show that the empirical patterns revealed in China are consistent with our model's predictions.

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Section: Introductionsupporting

confidence: 90%

Towards a dynamic model of the industrial upgrading with global value chains

Shen

Zhang

et al. 2020

World Economy

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“…A reasonable number of research have also particularly examined how tourism impacts the environment. Examples include Gössling et al (2002), Peeters et al (2007), Howitt et al (2010), Lee and Brahmasrene (2013), Solarin (2014), Al-Mulali et al (2015), De Vita et al (2015), Keng et al (2020) and Porto and Ciaschi (2020). Gössling et al (2002) created a methodological framework for the estimation of tourism-related ecological footprints.…”

Section: Literature Reviewmentioning

confidence: 99%

An asymmetric examination of the environmental effect of tourism in China

Olasehinde‐Williams

Ibikunle

2021

Tourism Economics

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This article employs the non-linear autoregressive distributed lag model in analysing the environmental impact of tourism in China from 2002Q1 to 2018Q4, while controlling for non-renewable energy consumption, trade openness, urbanisation, per capita GDP and its quadratic form. The approach permits the simultaneous testing of non-linearities in the short and long run. This is achieved through negative and positive partial sum decompositions of the regressor of interest. Findings from the article indicate the following: (i) long-run co-movements exist between tourism activities and environmental performance in China, (ii) tourism activities considerably damage the environment in China, (iii) the environment responds to tourism in an asymmetric manner, such that the damage caused by increasing tourism is smaller than the positive environmental effect of decline in tourism. Thus, less tourism protects the environment faster than more tourism damages it. A supplementary non-parametric test for non-linear causality was also performed. The result further provides strong evidence of a non-linear feedback causality between tourism activities and environmental performance in China in the first moment (mean) and second moment (variance). Tourism (environmental performance) is thus a significant predictor of China’s environmental performance (tourism).

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“…The proposed argument in our paper to some degree echoes their opinions in the sense that the larger size of local SOEs can generate a higher investment level, which raises the taxation level for the state. As a result, the state might provide more subsides for SOEs for the sake of efficiency improvement (Keng et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Unlocking the myths of size expansion in China's large state‐owned enterprises: Theory and evidence

Shen

2022

Manage Decis Econ

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This research proposes a theoretical framework to illustrate the incentives behind the exponential growth in asset size of China's large state-owned enterprises (SOEs) in the past few decades, with results presenting three types of incentives that led to their expansion. (1) The business empire building effect. (2) The state predatory effect. (3) A state benevolent effect in which the state is also concerned with "social welfare" in terms of increasing labor hiring through a larger asset size of SOEs for the

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Bilateral Rent‐seeking and Growth of Fdi Inflow in China: Theory and Evidence

Cited by 9 publications

References 62 publications

Towards a dynamic model of the industrial upgrading with global value chains

Towards a dynamic model of the industrial upgrading with global value chains

An asymmetric examination of the environmental effect of tourism in China

Unlocking the myths of size expansion in China's large state‐owned enterprises: Theory and evidence

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